Although arithmetic tutoring narrows the achievement gap between at-risk 1st graders and low-risk classmates on arithmetic problems, the gap for word-problem (WP) achievement steadily widens over the course of that tutoring. This is alarming because WP performance, an early form of complex mathematical reasoning, is the best long-term math predictor of employment and wages in adulthood and because scientific knowledge about early WP development lags behind arithmetic. The focus of this renewal is an innovative approach to preventing WP difficulty by embedding tutoring on language comprehension (LC), a cognitive resource associated with WPs, in the same academic material used to build WP skill. At-risk children are randomly assigned to 4 conditions. WP tutoring alone (the conventional, validated approach) is designed to compensate for limitations in working memory & reasoning. Embedded LC+WP tutoring (the innovative approach) is designed to strengthen LC while compensating for limitations in working memory & reasoning. Arithmetic tutoring is included to assess whether WP, arithmetic, & number knowledge learning is superior for either or both WP tutoring conditions compared to arithmetic tutoring. No tutoring is included to control for maturation and classroom instruction. At-risk children are followed through grade 3. Low-risk classmates are followed on the same measures at the same time points to assess achievement gaps. Aim 1 is to assess the efficacy of embedded LC+WP tutoring for promoting WP, arithmetic, & number knowledge outcomes and for narrowing the achievement gap in these domains. Aim 2 is to increase understanding about the role of LC, working memory, and reasoning in WP & arithmetic performance. This renewal has the potential to impact science by providing experimental evidence about the role of LC in WPs and insight into the process by which individual differences in LC, working memory, & reasoning interact with different forms of intervention on different math outcomes. The goal is to improve clinical practice by expanding the framework for preventing mathematics difficulty specifically and academic difficulty generally by assessing the added value of embedded cognitive resource training. If successful, we create the basis for scientific work on other forms of embedded cognitive resource training to extend the framework for academic intervention. This effort also provides a platform for transdisciplinary work across learning sciences, speech-language sciences, cognitive psychology, text comprehension, and learning disabilities. This transdisciplinary work is critical because current evidence indicates that LC difficulty negatively impacts response to academic intervention.